Nima Chamyani
About me
I am a medical-turned-researcher, driven by the belief that combining medical expertise with computational innovation can transform how we diagnose, monitor, and treat any disorders. My journey began with a PharmD degree from Iran and evolved through a MSc in Medical Modelling and Bioinformatics from Uppsala University, and has now led me to pursue a PhD at Karolinska Institutet at the intersection of medical science and artificial intelligence.
At Karolinska Institutet, I focus on computational neuroimaging, particularly leveraging deep learning techniques to improve the analysis and interpretation of brain MRI and photon-counting CT (PCCT) data. My mission is simple yet ambitious: To bridge the gap between cutting-edge technology and practical clinical applications, making advanced neuroimaging more accessible to a broader patient population.
Outside the lab, I’m an ardent advocate for open source projects and open science. By developing shareable tools and workflows, I aim to contribute to a collaborative development ecosystem—one in which knowledge flows freely and problems are tackled collectively. When I’m not immersed in my duties at KI or in brain scans, you’ll find me exploring Sweden’s trails or tinkering with open-source projects.
Research
- Computational Neuroimaging: Developing AI-driven pipelines for automated segmentation of brain structures in photon-counting CT and MRI.
- Machine Learning for Healthcare: Building multimodal models that fuse imaging, cognitive, and biomarker data to predict disease trajectories.
- Translational Bioinformatics: Applying graph representation learning and network medicine to uncover hidden patterns in complex biomedical data.
All other publications
- Conference publication: MULTIPLE SCLEROSIS JOURNAL. 2024;30(3):539
- Conference publication: MULTIPLE SCLEROSIS JOURNAL. 2024;30(3):524
Employments
- Phd Student, Department of Clinical Neuroscience, Karolinska Institutet, 2025-2026
- Research Assistant, Department of Clinical Neuroscience, Karolinska Institutet, 2024-2025